A system and method for identifying individuals that compatibly contribute to high-performing teams is disclosed. Teams may range in size and complexity from a two-person team of roommates to many hundreds in a commercial product development team. Candidates for new or existing teams are identified by matching brainwave response of candidates to the brainwave signature of high-performing, compatible teams. The stimuli of stimulus datasets are rapidly presented to candidates and sensed by any of the five human senses. The signature of a team type is a set of brainwave response characteristics extracted from one or more high-performing, compatible exemplar teams presented with the stimulus dataset and is also distinctly different from other team types or the general population. Closeness of fit between a candidate's brainwave response and the signature of the exemplar team provides an indication of the likely compatible fit and contribution of a candidate to a high-performing team.

The present invention relates to sedation assessment. In order to facilitate sedation depth monitoring in an autonomous imaging setting, it is proposed to use the imaging modality itself to measure the response to suitable reflexes in order to determine the depth of sedation wherein suitable reflexes include, but are not limited to, the pupil reflex, so-called superficial reflexes and the withdrawal reflexes. In one embodiment, the pupil reflex may be measured in an MRI system by repeated interleaving of dedicated iris MR imaging with the conventional scan protocol. In another embodiment, superficial reflexes in response to stroking of the skin may be measured. This may involve a dedicated actuator that may be closely integrated with the imaging modality, e.g. an MR receive coil applied to the patient. Alternatively, remote haptic systems may be used. The reflex is then acquired with a suitable diagnostic imaging method. In another embodiment, the withdrawal reflex in response to pain may be measured. This may involve an actuator that induces sudden stitching pain or very local temperature-induced pain and that is closely integrated with the imaging modality, e.g. a pinching device integrated with a patient support or an MR receive coil applied to the patient. The reflex is then acquired with a suitable diagnostic imaging method.

Embodiments herein relate to ear-worn devices and, more specifically, ear-worn devices that can measure reaction and/or reflex speeds. An ear-worn device herein can include a control circuit, a clock circuit in electrical communication with the control circuit, a motion sensor in electrical communication with the control circuit, an electroacoustic transducer for generating sound in electrical communication with the control circuit, and a power supply circuit in electrical communication with the control circuit. The ear-worn device can be configured to initiate generation of a stimulus sufficient to generate a response from the ear-worn device wearer. The ear-worn device can be configured to monitor for a qualified response to the stimulus and measure an amount of time between the stimulus and the qualified response. Other embodiments are also included herein.

Provided are an Eye Movement analysis with Hidden Markov Model (EMHMM) with co-clustering, an Eye Movement analysis with Switching Hidden Markov Models (EMSHMM) to analyze eye movement data in cognitive tasks involving stimuli with different feature layouts and cognitive state changes, a switching hidden Markov model (SHMM) to capture a participant's cognitive state transitions during the task and an EMSHMM to assess preference decision-making tasks with two or more cognitive states. The EMSHMM provides quantitative measures of individual differences in cognitive behavior/style, making a significant impact on the use of eye tracking to study cognitive behavior across disciplines.

A method for managing sleep of a user comprises obtaining, by a computing system, sleep data and environmental data for the user; determining, by the computing system, a sleep state of the user based on the sleep data; determining, by the computing system, one or more awakening actions based on the sleep state of the user and the environmental data; and causing one or more devices in an environment of the user to perform the one or more awakening actions to awaken the user.

A cognitive impairment diagnostic apparatus includes: a display which displays a video for diagnosis of cognitive impairment on a display surface; an imaging unit which captures images of an eye of a subject; a detection unit which detects viewpoints of the subject on the display surface in time series based on the images captured by the imaging unit; a creation unit which creates a distribution map representing a distribution of the viewpoints detected by the detection unit; a storage unit which stores case characteristic data indicating a characteristic of a viewpoint distribution corresponding to a typical case in cognitive impairment; and a diagnostic unit which diagnoses cognitive impairment of the subject by determining whether the distribution map has the characteristic indicated by the case characteristic data.

Examples of the present subject matter provide techniques for measuring stress levels using a variety of physiological indicators, such as pupil diameter, voice, cortisol levels, skin resistance, etc. Different sensors may be provided to measure the physiological indicators. Those measurements may be collected at a central server, where those measurements may be analyzed to determine the stress level of the user.

Systems and methods for performing psychological assessment are provided. An initial visual stimulus is selected and a series of steps are iteratively performed until associated confidence values for each of a plurality of indices meet a threshold value. The selected visual stimulus is provided at the display. Gaze tracking data is received from a remote eye tracking device in response to the selected stimulus being displayed to a patient. A deviation of the gaze tracking data from a standard response is determined. A score and the associated confidence value for at least one of the plurality of indices are adjusted based on the determined deviation of the gaze tracking data from the standard response. A new visual stimulus is selected based on the confidence values of the plurality of indices. Respective scores for the plurality of indices are provided to a user.

A method for selecting an AI solution for an automated robotic process including receiving at least one functional media including information indicative of brain activity by a human engaged in a task of interest, analyzing the functional media, identifying an activity level in at least one brain region, identifying a brain region parameter and an activity parameter; identifying an action parameter based in part on the brain region parameter or the activity parameter; and selecting a component of the AI solution in part on the brain region parameter, the activity parameter, or the action parameter.

A rider state modification system for improving a state of a rider in a vehicle includes a first neural network that operates to classify a state of the vehicle through analysis of information about the vehicle captured by an Internet-of-things device during operation of the vehicle. The rider state modification system further includes a second neural network that operates to optimize at least one operating parameter of the vehicle based on the classified state of the vehicle, information about a state of a rider occupying the vehicle, and information that correlates vehicle operation with an effect on rider state.